Dade exponential martingale converse We know that if $M$ is a continuous local martingale then the Dade exponential $\exp(\lambda M_t - \frac{\lambda^2}{2}\langle M,M \rangle_t)$ is also a continuous local martingale for all $\lambda$.  The book I am working from leaves as an exercise the following converse: 

If $M$ is adapted and continuous, $A$ is an adapted continuous process of finite variation, and $Z_t^\lambda := \exp(\lambda M_t - \frac{\lambda^2}{2}A_t)$ is a local martingale for all $\lambda \in \mathbb{R}$, then $M$ is a local martingale and $\langle M,M \rangle = A$.

Based on a hint in the book, I computed
$$
\left.\frac{\partial}{\partial \lambda} Z_t^{\lambda} \right\rvert_{\lambda=0} = \left.(M_t - \lambda A_t)Z_t^\lambda\right\rvert_{\lambda=0} = M_t
$$
so from the definition of differentiability we have 
$$
\lim_{\lambda \rightarrow 0} \left( \frac{Z_t^\lambda-1}{\lambda} \right) = M_t
$$
for all $t$.  Since each $\frac{Z_t^\lambda-1}{\lambda}$ is a local martingale this implies $M_t$ is the limit of local martingales, but I'm not sure if that is enough to show $M_t$ is as well.  If this method works, then showing $\langle M,M\rangle = A$ can be done with the same method by taking a second derivative.  
Does this work to show $M$ is a local martingale?  If not, what is the proper method and way to use the hint?
EDIT: The book is Continuous Martingales and Brownian Motion by Revuz and Yor
 A: I came up with a different way to prove it that doesn't use the derivative or convergence results:
By continuity of $M_t$ and $A_t$, $Z_t > 0$ a.s. so we can take the log to find $M_t = \log(Z_t^1) + \frac 12 A_t$ is a semi-martingale.  Therefore $M_t = M_0 + N_t + B_t$ where $N_t$ is a local martingale and $B_t$ is a process of finite variation.  Applying Ito's formula to $Z_t$ yields
\begin{align*} dZ_t^\lambda &= \lambda Z_t^\lambda dM_t - \frac{\lambda^2}{2} Z_t^\lambda dA_t + \frac{\lambda^2}{2} Z_t^\lambda d\langle M,M \rangle_t \\
&= \lambda Z_t^\lambda dN_t + Z_t^\lambda \left( \lambda dB_t - \frac{\lambda^2}{2} dA_t + \frac{\lambda^2}{2} d\langle M,M \rangle_t \right) \\
&= \lambda Z_t^\lambda dN_t
\end{align*}
because a local martingale must have no drift terms.  Since $e^{\lambda N_t - \frac{\lambda^2}{2} \langle N,N \rangle_t}$ is the unique solution to $dX_t = \lambda X_t dN_t$, this gives that $$Z_t^{\lambda} = e^{\lambda N_t - \frac{\lambda^2}{2} \langle N,N \rangle_t} = e^{\lambda M_t - \frac{\lambda^2}{2} A_t} = e^{\lambda N_t + \lambda B_t - \frac{\lambda^2}{2} A_t}, $$ so $B_t = \frac{\lambda}{2}(A_t - \langle N,N \rangle_t)$.  Since this holds for all $\lambda \in \mathbb{R}$, we must have that both sides are $0$ so $M_t = N_t$ and $A_t = \langle N,N \rangle_t = \langle M,M \rangle_t$.
